Method of indexing entities

ABSTRACT

An index to a plurality of entities is built, where each entity is represented by a point defined in a space. Entities whose points are furthest apart are identified. A first area is created, the extremities of which first area are given by the points representing the identified entities. Entities falling within the first area are assigned to a storage area corresponding to the first area. The first area is divided into a plurality of second areas. For each of the plurality of second areas, a. each of the plurality of second areas is linked to the first area, and, b. the above steps are repeated until the first area includes a single point. Storage areas corresponding to each of the first area are then written to the index.

This application is the US national phase of international application PCT/GB01/05486 filed 11 Dec. 2001 which designated the U.S.

BACKGROUND

1. Related Art

The present invention relates to a method of indexing for use with entities stored in a database.

2. Related Art

It can readily be seen that when there are vast numbers of entities in a database, identifying entities in accordance with a query in respect of data in the database within a reasonable period of time is a non-trivial exercise. To ease the retrieval process, data in a database is generally indexed in some way, and queries are then performed on the index. The way in which the entities are indexed can be expected to have a significant bearing on the quality and speed of retrieval, and as information is increasingly being stored in databases, there is significant interest in finding improved ways of indexing data.

It is known to index location data based on place names. It is also known to retrieve a set of geographic coordinates from place names, and build an index based on topological information extracted from the coordinates (e.g. “GIPSY”: developed at U.C. Berkeley in conjunction with a joint NSF/NASA/ARPA (Wilensky et al., 1994) initiative). Furthermore, it is known to build an index based on the geographical coordinates themselves: database vendors such as Oracle™ have developed systems for storing and indexing geometrical data—e.g. Oracle spatial data cartridge, which allows a spatial querying to be carried out using an extended (non-standard) form of SQL. Other vendors, like MapInfo™, SpatialWare™, Innogistic™ and Informix™ have similar proprietary ways of dealing with spatial data. In particular, Innogistic™ have developed a product known as Cartology DSI, which stores geometrical vector data as blobs (binary large objects—which are not intrinsically recognisable by the underlying database). It also creates indexes outside of the database based on the well-known ‘quad tree’ idea. The index data is stored in binary-tree structures and is accessed by DCOM middleware services.

Both the Oracle™ and Innogistic™ systems make use of the quad-tree method, in which an entire area of a layer is divided and subdivided into a series of four nested squares. The entire area is assigned to one of four squares designated 0, 1, 2, and 3. Each of these squares is subdivided into four smaller squares. The area of square 1 becomes 10, 11, 12, and 13. Each of these is further subdivided, meaning, for example, that the subdivisions of square 11 would be assigned index values of 110, 111, 112, and 113. As a result, any location in the map can be referred to by a single index number. The disadvantage with this quad-tree method is that processing time is wasted if there are no points within the subdivided squares; if indexing is performed over a large area, this wasted processing time is non-trivial and costly.

According to a first aspect of the present invention there is provided a method of building an index to a plurality of entities, wherein each entity is represented by a point defined in a space. The method comprises the steps of:

-   -   i) identifying entities whose points are furthest apart;     -   ii) creating a first area, the extremities of which first area         are given by the points representing the identified entities;     -   iii) assigning entities falling within the first area to a         storage area corresponding to the first area;     -   iv) dividing the first area into a plurality of second areas;     -   v) for each of the plurality of second areas,         -   a. linking each of the second areas to the first area, and         -   b. repeating steps (i)-(v) until the first area includes a             single point; and     -   vi) writing the storage areas corresponding to each of the first         areas to the index.

By identifying points that are spaced furthest apart, the indexing method essentially “shrinks” the indexing space so that it only indexes over areas that contain points. Thus the storage areas are correspondingly compact, which has advantages in terms of minimising use of storage space.

The second areas can be linked to first areas via a so-called “linked list” of points, which is an efficient linking mechanism known in the art.

Preferably the first area is divided into four second areas in step (iv) and step (v) is repeated recursively for each of the second areas. Advantageously the identifying step (i) comprises the steps of

calculating distances between entities in each of two dimensions; and

for each of the dimensions identifying which of the entities has the greatest distance between them, such that when the two dimensions are perpendicular to one another the first area created in step (ii) is a rectangle, defined by at least two points.

Conveniently the method further includes the steps of writing the or each entity within each of the first areas to a database, maintaining a register of number of entities written to the database, and for each of the first areas, writing the current register number to the storage area corresponding to the first area.

BRIEF SUMMARY

Advantageously entities that have been indexed in accordance with the first aspect of the invention can be retrieved. In particular, and in terms of the points corresponding to the entities, points that are contained by a predetermined area can be retrieved by performing the following steps:

(a) identifying one or more regions that are contained by the predetermined area, each region encompassing one or more points and being associated with linking data which, for each region, identifies the point or points encompassed by that region; and

(b) accessing linking data corresponding to the identified regions so as to retrieve points encompassed by the identified regions.

The regions correspond to the storage areas indexed in accordance with the first aspect of the invention. Thus as the storage areas are compact, in that, as described above, they are “shrink wrapped” around points, the identification of points in the index is an efficient process.

Preferably the identifying step (a) includes the steps of retrieving a first region; comparing extents of the first region with extents of the predetermined area in order to establish whether the first region overlaps with the predetermined area; and, if there is overlap, successively retrieving second regions, each of which second regions is contained by the first region. These steps of comparing and retrieval can be repeated for each second region until the overlap is such that the second region is wholly contained by the predetermined area.

Conveniently the plurality of points is pre-stored as a list of points in accordance with relationships between respective first and second regions, and the linking data includes a value indicating the position of a first of the corresponding encompassed points in the list of points. The accessing step (b) then comprises, for each of the identified regions: retrieving an identifier representative of the number of encompassed points and retrieving a position value associated with the identified region; and accessing the list of points and retrieving the number of encompassed points from a position in the list given by the position value.

Preferably the value involved in the linking data corresponds to the register number written to the storage area.

The method steps are preferably embodied in one or more computer programs, which may be wholly, or in part, embodied as a signal in a carrier wave for transmission over a communications network, and/or in a computer readable medium as a computer program product.

Conveniently the points correspond to data that can be expressed in two dimensions, for example location (longitude and latitude) data or range data. Range data can include business hours (e.g. opening and closing times), price margins (e.g. maximum and minimum prices), and/or medical data (e.g. maximum and minimum blood pressure). Thus a predetermined area could be a range of prices—such as a maximum house prices and a minimum house price. In accordance with the retrieval method described above, the extents of the predetermined area (i.e. price range) are compared with a region retrieved from the index. All regions that overlap with the price range are then successively retrieved until a region, which falls wholly within the specified price range, is identified. All points falling within this identified region thus represent goods being of a price that falls within the specified maximum and minimum price range.

Further aspects, features and advantages of the present invention will be apparent from the following description of preferred embodiments of the invention, which refers to the accompanying drawings, in which

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating aspects of a communications system used by the invention;

FIG. 2 is a schematic diagram showing an example of points to be indexed according to the invention;

FIG. 3 is a schematic diagram showing an expanded view of FIG. 2;

FIGS. 4 a & 4 b in combination comprise a flow diagram showing an embodiment of an indexing process according to the present invention when indexing the points shown in FIG. 2;

FIG. 5 is a schematic diagram showing application of the process of FIGS. 4 a & 4 b to create a quad around the points shown in FIG. 2;

FIG. 6 is a schematic diagram showing application of the process of FIGS. 4 a & 4 b to create a sub-quad of the quad created according to FIG. 5;

FIG. 7 is a schematic diagram showing application of the process of FIGS. 4 a & 4 b to create a sub-quad of one of the sub-quads of FIG. 6;

FIG. 8 is an expanded view of FIG. 7;

FIG. 9 is an expanded view of FIG. 8 showing application of the process of FIGS. 4 a & 4 b (where points labeled 1, 2 and 3 in FIGS. 4 a and 4 b are to be considered respectively connected when the FIGS. 4 a and 4 b are juxtaposed to create a complete flow-chart) to create another of the sub-quads shown in FIG. 7;

FIG. 10 is an expanded view of FIG. 8 showing application of the process of FIGS. 4 a & 4 b to create another of the sub-quads shown in FIG. 7;

FIG. 11 is a schematic diagram showing application of the process of FIGS. 4 a & 4 b to create another sub-quad of one of the sub-quads of FIG. 6;

FIG. 12 is a schematic diagram illustrating a process of storing points according to the invention;

FIGS. 13 a & 13 b (where points labeled 1, 2 and 3 in FIGS. 13 a, 13 b are to be considered respectively connected when the FIGS. 13 a, 13 b are juxtaposed to create a complete flow-chart) in combination comprise a flow diagram showing an embodiment of a retrieving process according to the present invention when retrieving points in accordance with an area of interest;

FIG. 14 is a schematic diagram showing an example of an area of interest for which points are to be retrieved;

FIG. 15 is a schematic diagram showing application of the process of FIGS. 13 a & 13 b to one of the sub-quads of FIG. 6;

FIGS. 16 and 17 are an enlarged view of FIG. 15 and are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to a first of the sub-quads of FIG. 7;

FIG. 18 is an enlarged view of FIG. 15 and shows the area of interest and a second of the sub-quads of FIG. 7;

FIG. 19 is a schematic diagram corresponding to FIG. 18 showing application of the process of FIGS. 13 a & 13 b to the second of the sub-quads of FIG. 7;

FIGS. 20 a & 20 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to a (first) sub-quad of the sub-quad shown in FIG. 18;

FIGS. 21 a & 21 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to another (a second) sub-quad of the sub-quad shown in FIG. 18;

FIGS. 22 a & 22 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to another sub-quad (a third) of the sub-quad shown in FIG. 18;

FIGS. 23 a & 23 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to another sub-quad (a fourth) of the sub-quad shown in FIG. 18;

FIG. 24 is an enlarged view of FIG. 15 and shows the area of interest and a third of the sub-quads of FIG. 7;

FIG. 25 is a schematic diagram corresponding to FIG. 24 showing application of the process of FIGS. 13 a & 13 b to the third of the sub-quads of FIG. 7;

FIGS. 26 a & 26 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to a (first) sub-quad of the sub-quad shown in FIG. 24;

FIGS. 27 a & 27 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to another (a second) sub-quad of the sub-quad shown in FIG. 24;

FIGS. 28 a & 28 b are schematic diagrams showing application of the process of FIGS. 13 a & 13 b to another sub-quad (a third) of the sub-quad shown in FIG. 24;

FIG. 29 is a schematic diagram showing application of the process of FIGS. 13 a & 13 b to another sub-quad (a fourth) of the sub-quad shown in FIG. 24;

FIG. 30 is an enlarged view of FIG. 15 and shows the area of interest and a fourth of the sub-quads of FIG. 7; and

FIG. 31 is a schematic diagram corresponding to FIG. 30 showing application of the process of FIGS. 13 a & 13 b to the fourth of the sub-quads of FIG. 7.

FIG. 32 is a flow diagram showing further steps involved in the retrieving process of FIGS. 13 a & 13 b; and

Each of FIGS. 33 a-33 e is a schematic illustration of a region of interest for which points are to be retrieved according to the invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENT Overview

Database servers DB1, DB2, such as those shown in FIG. 1, typically store information for retrieval by users. At the physical level, the communications environment within which the database servers DB1, DB2 are located includes at least one user interface, commonly provided by a computer terminal or workstation T3.

Embodiments of the invention can be executed on the workstation T3, which is connected to database servers DB1, DB2. Although the database servers DB1, DB2 are shown on the same LAN N1 as the terminal T3, it is understood that the database servers DB1, DB2 could be connected to different networks, which in turn are connected to LAN N1 via one or more switches and/or routers (not shown). Embodiments receive data as input, for instance as a file, and build an index to the data, as is described in more detail below. The built index is then saved in one of the databases DB1, DB2, and the indexed data is also saved, in an order given by the structure of the built index, to one of the databases DB1, DB2. The built index can be saved on the same, or a different, database as the database on which the data is stored.

Embodiments of the present invention are concerned with indexing entities that are defined by 2-dimensions. Obvious examples of entities that can be indexed according to embodiments include the location of objects, such as petrol stations, cash points etc., as the position of objects is commonly defined in terms of latitude and longitude. Many other entities can be represented by 2-dimensions—e.g. acceleration of a motorbike as a function of time and speed, conductivity of a material as a function of material properties and temperature, deformation of an object as a function of material properties and force applied to the object etc. Furthermore, transformations can be applied to n-dimensional parameters to reduce them to 2-dimensional parameters, which can be displayed in a 2-dimensional space.

A further example of entities that can be indexed using embodiments of the present invention include range information, e.g. temporal information, price information, and medical condition information.

An example of temporal range information is opening and closing times of business and leisure establishments—these times can be expressed in two dimensions, with, for example, the closing and opening times respectively on the ordinate and abscissa axes. Similarly, delivery times (earliest and latest) can be expressed in two dimensions.

An example of price information includes prices of goods, so that, for example, maximum and minimum prices of goods can be respectively expressed on one of two dimensions, and so indexed using embodiments of the invention. Price information also includes trading information, as used to buy and sell stocks, shares, bonds etc.

An example of medical condition information includes statistics relating to measurable conditions such as body temperature and blood pressure, and conditions that can be translated into numerical representations, such as cancer sites.

In the following description, entities are generally referred to as “points” in order to disassociate the context of the entities (e.g. petrol station, cash point etc.) from the mechanics of the embodiment.

In overview, an embodiment of a method of indexing points is described with reference to FIG. 2. FIG. 2 shows an area R1 within which a plurality of points 200 is located. Each of the points is defined in x,y co-ordinate space. Essentially the area R1 comprising points to be indexed is examined and split into areas R3, R4 containing points and area R2 between lines L1 and L2 not containing points (the areas could be split into any shape, such as a rectangle, triangle, or strips; FIG. 2 shows the areas split into strips for the purposes of describing the inventive concept of this invention). The embodiment then examines the distribution of points in areas R3 and R4, identifying on a smaller scale than was considered for region R1 areas in R3 and R4 that comprise points. Referring to FIG. 3, R4 essentially becomes R11 and the distribution of points within R11 is examined (e.g., by noting the absence of points within central region R12 located between regions R13 and R14). By concentrating on the distribution of points in this way, areas that do not contain any points, Region R2 in FIG. 2 and region R12 between lines L11 and L12 in FIG. 3 are implicitly discarded. The process is continually repeated, effectively “burrowing down” through a series of areas of diminishing size, until the size of an area is such that it collapses to the size of a single point. As the embodiment “burrows down”, each area is linked to the area above it, such that each point is linked by a series of areas. An index to these points comprises the series of areas, and these areas and points are used to create an index (described in more detail below) that is saved in database DB1. The relationship between the points and areas enables points to be identified by identification of an area in the index.

One of the advantages of creating an index as described above is that the query search domain is confined to areas that are known to contain points—i.e. queries will only be carried out on the areas saved in the database DB1, and as these areas by definition include points, the search domain is relatively compact. Referring back to FIG. 2, the process of identifying points in respect of a query is faster according to the embodiment described above, than if the index comprised information relating to the whole of area R1.

In a particular form of an embodiment, presented below with reference to FIGS. 4-11, points are 2-dimensional co-ordinates in x, y space. If the entities to be indexed are acceleration values, defined by a corresponding set of time and speed values, the time and speed values map directly onto an x,y co-ordinate space, so that (t1, v1), (t2, v2) . . . (tn, vn) are co-ordinates of points corresponding to the acceleration values. Similarly, if the entities to be indexed are location values, defined by a corresponding set of latitude and longitude values, the latitude and longitude values map directly onto an x, y co-ordinate space, such that (lat_(—)1, long_(—)1) . . . (lat_n, long_n) are co-ordinates of points corresponding to location values. It is assumed that the points have been stored (e.g. written to a file), so that embodiments of the invention read the points in from a file. In alternative embodiments a user may input the points when the index to those points is about to be built.

Furthermore, in the embodiment presented below, the areas are squares, referred to as “quads” and “sub-quads” in the description below, and each quad is successively split into four sub-quads. Each sub-quad is examined for the existence of points. Those with no points are discarded, which is an equivalent process to discarding the area R2 described with reference to FIGS. 2 and 3 above, and each new sub-quad containing points is “shrunk wrapped” around the smallest area that contains points in that sub-quad. (The embodiment analyses the areas in accordance with squares, but many other shapes could be used to “shrink-wrap” around the points). Each sub-quad is then divided again into four sub-quads, empty sub-quads are again discarded and each remaining sub-quad “shrunk-wrapped” about its smallest area containing points. Eventually, each remaining sub-quad will have been “shrunk-wrapped” onto a single point and its co-ordinates will be those of the point concerned. Once the quad and all the sub-quads, including both the intervening sub quads which haven't been discarded and the sub-quads coinciding with single points, have been identified, an index to the points, comprising the quad and sub quads relevant to each one, is created. This is described in detail after the discussion of FIGS. 5-10.

In the following, steps S 4.1 through to S 4.9 are shown in sequence in the flow chart of FIGS. 4 a and 4 b and illustrated by the operations with the same reference numerals as shown in FIGS. 5-11.

FIG. 5

-   -   Step S4.1 Read in x, y co-ordinates of all points to be indexed         (as stated above, the points may be read from either a storage         location, such as a file, or directly from a user);     -   Step S4.2 Draw up a bounding box for all points, identifying,         and “shrink-wrapping” around, the co-ordinates of the outermost         points (the bounding box is given by the difference between the         co-ordinates of the outermost points in both the x and y         dimensions: dx and dy respectively). This bounding box is the         outermost quad 501;     -   Step S4.3 & Step S4.4 Save extents of quad 501—i.e. dx, dy—and         the co-ordinates of the points in it;     -   Step S4.5 Check whether the outermost quad 501 has positive size         (i.e. are dx, dy of quad 501 equal to zero?) In the example         shown in FIG. 5, there is an outermost quad 501, because the         quad has multiple points in it, dx, dy are non-zero, and thus         quad 501 has positive size;     -   Step S4.6 Split the outermost quad 501 into four sub-quads, 503         a, 503 b, 503 c, 503 d;     -   Step S4.6.1 Tag each point with its relevant sub-quad and record         the number of points in each sub-quad;     -   Step S4.7 Starting with sub-quad 0 (503 a) check whether there         are any points in the sub-quad 503 a.         As there are points, input the points within this sub-quad 0         (503 a) to Step S4.1 and run through steps Step S4.1 onwards for         sub-quad 0 (503 a), as described below with reference to FIG. 6.         FIG. 6     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 503 a;     -   Step S4.2 Draw up bounding box for all points in 503 a, creating         “shrink-wrapped” sub-quad 0 601. This illustrates the principle         described above—the embodiment identifies an area within         sub-quad 0 where there are no points, and this area is then         discarded;     -   Step S4.3 & Step S4.4 Save extents of sub-quad 0 (601)—i.e. dx,         dy—and the co-ordinates of points in it;     -   Step S4.5 Check whether sub-quad 601 has positive size? (i.e.         are dx, dy of quad 601 equal to zero?) As can be seen in FIG. 6,         quad 601 has multiple points in it, dx, dy for quad 601 are         non-zero, and thus sub-quad 601 has positive size;     -   Step S4.6 Split sub-quad 0 601 into 4 sub-quads: 0,0 (603 a),         0,1 (603 b), 0,2 (603 c), 0,3 (603 d)     -   Step S4.6.1 Tag each point with its relevant sub-quad and record         the number of points in each sub-quad;     -   Step S4.7 Starting with sub-quad 0,0 (603 a) Check whether there         are any points in the sub-quad 0,0 (603 a): As there are points,         input the points within this sub-quad 0,0 (603 a) to Step S4.1         and run through steps Step S4.1 onwards for sub-quad 0,0 (603         a), as described below with reference to FIG. 7.         FIG. 7     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 603 a;     -   Step S4.2 Draw up bounding box for all points in sub-quad 0,0         (603 a), creating “shrink-wrapped” sub-quad 0,0 701. As for         sub-quad 0, the area without points within sub-quad 603 a is         ignored;     -   Step S4.3 & Step S4.4 Save extents of sub-quad 0, 0 (701)—i.e.         dx, dy—and the co-ordinates of points in it;     -   Step S4.5 Check whether sub-quad 701 has positive size? (i.e.         are dx, dy of quad 701 equal to zero?) As can be seen in FIG. 7,         quad 701 has multiple points in it, dx, dy for quad 701 are         non-zero, and this sub-quad 701 has positive size;     -   Step S4.6 Split sub-quad 0,0 701 into 4 sub-quads: 0,0,0 (703         a), 0,0,1 (703 b), 0,0,2 (703 c), 0,0,3 (703 d)     -   Step S4.6.1 Tag each point with its relevant sub-quad and record         the number of points in each sub-quad;     -   Step S4.7 Starting with sub-quad 0,0,0 (703 a) check whether         there are any points in the sub-quad 0,0,0 (703 a): there is one         point in sub-quad 0,0,0 (703 a) so input the points within this         sub-quad 0,0,0 to Step S4.1 and run through steps Step S4.1         onwards for sub-quad 0,0,0 (703 a), as described below with         further reference to FIG. 7.         Also FIG. 7     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 703 a;     -   Step S4.2 Draw up bounding box for all points in sub-quad 0,0,0         (703 a), creating “shrink-wrapped” sub-quad 0,0,0: here around a         single point;     -   Step S4.3 & Step S4.4 Save the extents of the “shrink-wrapped”         sub-quad 0,0,0, which is now down to a single point such that         dx, dy=0, and save the co-ordinates of the point;     -   Step S4.5 Check whether sub-quad the point has positive size?         (i.e. are dx, dy of the point equal to zero?) In fact dx and dy         are both zero because the sub-quad 703 a collapsed into a single         point. So onto Step S4.8;     -   Step S4.8 Increment the sub-quad counter i at this level         (0,0,i), input the points (Step S4.7) within sub-quad 0,0,1 (703         b) to Step S4.1 and run through steps Step S4.1 onwards for         sub-quad 0,0,1 (703 b), as described below with reference to         FIG. 8.         FIG. 8     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 703 b;     -   Step S4.2 Draw up bounding box for all points in sub-quad 0,0,1         (703 b) creating “shrink-wrapped” sub-quad 0,0,1 801. As for         sub-quad 0, the area without points within sub-quad 703 b is         ignored;     -   Step S4.3 & Step S4.4 Save extents of sub-quad 801—i.e. dx,         dy—and the co-ordinates of points in it;     -   Step S4.5 Check whether sub-quad 801 has positive size? (i.e.         are dx, dy of quad 703 a equal to zero?). Sub-quad 801 has         multiple points in it, dx, dy for quad 801 are non-zero, and         thus sub-quad 801 does have positive size;     -   Step S4.6 Split sub-quad 0,0,1 801 into 4 sub-quads: 0,0,1,0         (803 a), 0,0,1,1 (803 b), 0,0,1,2 (803 c), 0,0,1,3 (803 d)     -   Step S4.6.1 Tag each point with its relevant sub-quad and record         the number of points in each sub-quad;     -   Step S4.7 Starting with sub-quad 0,0,1,0 (803 a) Check whether         there are any points in the sub-quad 0,0,1,0 (803 a): There are         no points in sub-quad 0,0,1,0 (803 a);     -   Step S4.8 Increment the sub-quad counter i at this level         (0,0,1,i) and input the points (Step S4.7) within sub-quad         0,0,1,1 (803 b) to Step S4.1 and run through steps Step S4.1         onwards for sub-quad 0,0,1,1 (803 b), as described below with         reference to FIG. 9.         FIG. 9     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 803 b;     -   Step S4.2 Draw up bounding box for all points in sub-quad         0,0,1,1 (803 b), creating “shrink-wrapped” sub-quad 0,0,1,1,         which is a single point;     -   Step S4.3 & Step S4.4 Save extents of the single point—i.e. dx,         dy—and the co-ordinates of the point;     -   Step S4.5 Check whether the point has positive size? (i.e. are         dx, dy of the point equal to zero?) In fact dx and dy are both         zero because the sub-quad 803 b collapsed into a single point.         So onto Step S4.8;     -   Step S4.8 Increment the sub-quad counter i at this level         (0,0,1,i) and input the points within sub-quad 0,0,1,2 (803 b)         to Step S4.1 and run through steps Step S4.1 onwards for         sub-quad 0,0,1,2 (803 b), as described with further reference to         FIG. 9         Also FIG. 9     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 803 c;     -   Step S4.2 Draw up bounding box for all points in sub-quad         0,0,1,2 (803 c), creating “shrink-wrapped” sub-quad 0,0,1,2,         which is a single point;     -   Step S4.3 & Step S4.4 Save extents of the single point—i.e. dx,         dy—and the co-ordinates of the point;     -   Step S4.5 Check whether the point has positive size? (i.e. are         dx, dy of the point equal to zero?) In fact dx and dy are both         zero because the sub-quad 803 c collapsed into a single point.         So onto Step S4.8;     -   Step S4.8 Increment the sub-quad counter i at this level         (0,0,1,i). There are no points (Step S4.7) within sub-quad         0,0,1,3 (803 d), so back to Step S4.8: increment the sub-quad         counter i at this level (0,0,1,i): but i>3 so     -   Step S4.9 Return to sub-quad level 0,0,i and increment the         sub-quad counter from 1 to 2, and thus consider sub-quad 0,0,2         (703 c): There is a point in sub-quad 0,0,2 (703 c) so input the         points (Step S4.7) within sub-quad 0,0,2 (703 c) to Step S4.1         and run through steps Step S4.1 onwards for sub-quad 0,0,2 (703         c), as described with reference to FIG. 10.         FIG. 10     -   Step S4.1 Read in x, y co-ordinates of points corresponding to         sub-quad 703 c;     -   Step S4.2 Draw up bounding box for all points in sub-quad 0,0,2         (703 c), creating “shrink-wrapped” sub-quad 0,0,2, which is a         single point;     -   Step S4.3 & Step S4.4 Save extents of the single point—i.e. dx,         dy—and the co-ordinates of the point;     -   Step S4.5 Check whether the point has positive size? (i.e. are         dx, dy of the point equal to zero?) In fact dx and dy are both         zero because the sub-quad 703 c collapsed into a single point.         So onto Step S4.8;     -   Step S4.8 Increment the sub-quad counter i at this level (0,0,         i). There are no points (Step S4.7) within sub-quad 0,0,3 (703         d), so back to Step S4.8: increment the sub-quad counter i at         this level (0,0,i): but i>3 so     -   Step S4.9 Return to sub-quad level 0, i and increment the         sub-quad counter i from 0 to 1, and thus consider sub-quad 0,1         (603 b), as described with reference to FIG. 11.         FIG. 11         The process described in FIGS. 6-10 is repeated, but for         sub-quad 0,1, and once all of the points within sub-quad 0,n         have been assigned to sub-quads, the process moves onto sub-quad         1.

As described earlier, building an index to these points is then a matter of saving the sub-quad information. This can be engineered in many ways, but preferably the index comprises sub-quad information saved at steps S 4.3 and S 4.4, namely the extents of sub-quad (in x, y co-ordinates) and co-ordinates of points falling therein, and a link to the 4 sub-quadrants within the sub-quad. Thus the index essentially comprises a hierarchy of sub-quad structures where the hierarchy is given by the relationship between each successive sub-quad and its 4 sub-quads. The sub-quads are written to the index in accordance with the sub-quad hierarchy, from the largest sub-quad (here 501 on FIG. 5), down to the smallest sub-quad.

In addition to saving the sub-quad structures in the database DB1, the points are written to the database (either the same database or a different database), e.g. in a file, in an order given by the inverse of the sub-quad hierarchy. Thus in this case, points in the sub-quads at the bottom of the hierarchy are written to the file first. As the points are written to a file, a running tally of the total number of points (register of number of points) is maintained, such that as each point is written to the file, a counter representing:

current number of points encountered so far+1

is written to the respective sub-quad structure. The tally works from the smallest sub-quad up, and, for each sub-quad, essentially indicates the position of the first of all points in that sub-quad in terms of all of the points being indexed (Pos_(sub) _(—) _(quad)) e.g. Referring to FIG. 12,

Number of first point written to Highlighted Sub- sub-quad point in quad Points in sub-quad (N) (Pos_(sub) _(—) _(quad)) points file 0,0,1,1 n (N = 1) 1 n,m,p,o . . . 0,0,1,2 m (N = 1) 2 n,m,p,o . . . 0,0,0 p (N = 1) 3 n,m,p,o . . . 0,0,1 n, m (N = 2) 1 n,m,p,o . . . 0,0,2 o (N = 1) 4 n,m,p,o . . . 0,0 n,m,p,o (N = 4) 1 n,m,p,o . . . 0,1,c,d some points 5 n,m,p,o, Next . . .

Thus points file for sub-quad 501 (the outermost quad, see FIG. 5) reads n,m,p,o . . . (starting from the smallest sub-quad 0,0,1,1). As both the number of points, (N) and the number in the running tally of points (Pos_(sub) _(—) _(quad)) corresponding to the first point in a sub-quad, are written to the sub-quad, then once a sub-quad of interest has been identified, the points that lie within the identified sub-quad can be extracted by moving to Pos_(sub) _(—) _(quad) in the points file and extracting N points from that position. This is demonstrated in an embodiment demonstrating retrieval of points.

Retrieval of Information

The second invention relates to a method of retrieving entities by means of an index of elements related to the entities, when the relationship between each element and other elements in the index, and the relationship between elements in the index and the entities being indexed, is known. The method is readily applicable to an index created in accordance with the method of indexing presented above, because the index comprises a hierarchy of sub-quad structures, and the hierarchy is well defined (by quad->sub-quad relationships). However, it should be borne in mind that the method is equally applicable to any type of index that satisfies these conditions.

In the following description, an embodiment of the retrieval process is described, where an index to points is queried with a query specifying a “region of interest”. It is assumed that:

-   -   the elements in the index are a plurality of areas within a         predetermined area,     -   the entities being indexed are points defined by two dimensions;     -   there is a predetermined relationship between the areas; and     -   there is a predetermined relationship between the areas and the         points.         Essentially the embodiment identifies which of the areas     -   a) overlaps with the region of interest, and     -   b) contains points within those areas that overlap with the         region of interest.         The predetermined relationship between areas and the points is         then used to extract points falling within the identified areas.

A region of interest refers to a region within the two dimensional representation of the entity. Thus for the temporal range described above (closing and opening times of business and leisure establishments), a region of interest would be a time period of interest—such as “shops open between 10:00 and 13:00 hours”. The region of interest would then be defined by a region (preferably a square) bounded within prespecified points. Referring to FIGS. 33 a-e, the region of interest could be any one of:

(0,10), (13,24)≡establishments that are open sometime between 10:00 & 13:00 (FIG. 33 a)

(0,13), (10,24)≡establishments that are open continuously between 10:00 & 13:00 (FIG. 33 b)

(0,10), (10,13)≡establishments that are open before 10:00, but close before 13:00 (FIG. 33 c)

(10,13), (13,24)≡establishments that open after 10:00 but close after 13:00 (FIG. 33 d)

(10,10), (13,13)≡establishments that open after 10:00 & close before 13:00 (FIG. 33 e)

Similarly, for the pricing range described above, a region of interest would be a range of prices, so that, for a retrieval requirement of “all items that fall somewhere in the range of £50.00 and £80.00”, the region of interest could be defined by a region bounded within the points (0,50) and (80, 80).

For the location information described above, a region of interest would be a range of positions, such as “all items located between a first position ((lat, long)₁) and a second position ((lat, long)₂)”.

A flow diagram showing steps of a method of identifying areas that overlap with the region of interest, when the region of interest relates to location information, is shown in FIGS. 13 a and 13 b. The steps are then illustrated, for the region of interest shown in FIG. 14, in FIGS. 14-31. In this embodiment, specific examples of areas within a predetermined region are referred to as quads and sub-quads. The method steps shown in FIG. 13 are described below with reference to each of FIGS. 14-31.

FIG. 14

-   -   S13.1.1 Read in x, y co-ordinates of a region of interest         (x1,y1) (x2,y2). As an example, if a user wants to locate         garages in a certain area, these might be indexed as         latitude/longitude pairs defining points in a two-dimensional         space and the geographical area that the user is interested in         can be expressed as a “region of interest” in the         two-dimensional space;     -   S13.1.2 Retrieve co-ordinates of points and size of quad for the         outermost quad and set (X1_Q, Y1_Q) (X2_Q, Y2_Q) to size of         outermost quad;     -   S13.2 Assess whether the region of interest requires cropping:         if x1<X1_Q set x1=X1_Q; if y1<Y1_Q set y1=Y1_Q; if x2>X2_Q set         x2=X2_Q; if y2>Y2_Q set y2=Y2_Q. For the example region of         interest shown in FIG. 14, none of these conditions are         satisfied;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case neither         conditions are satisfied;         Steps S13.2 and S13.3 are only one example of conditions that         can be applied to establish whether the sub quad retrieved at         S13.1.2 overlaps with the region of interest, and whether, if         there is overlap, there are any points within the overlapping         region; it is envisaged that alternative methods could be         applied to establish this.     -   S13.4 Assess whether the region of interest overlaps exactly         with the quad. No:     -   S13.5 Retrieve a sub-quad (503 a) of the present quad (501) in         accordance with S13.1.2, as is described with reference to FIG.         15         FIG. 15     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0 601: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 601;     -   S13.2 Assess whether the region of interest requires cropping:         if x1<X1_Q set x1=X1_Q; if y1<Y1_Q set y1=Y1_Q; if x2>X2_Q set         x2=X2_Q; if y2>Y2_Q set y2=Y2_Q. In this case none of these         conditions are satisfied;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case neither         conditions are satisfied;     -   S13.4 Assess whether the region of interest overlaps exactly         with the sub-quad. No:     -   S13.5 Retrieve a sub-quad of the present sub-quad in accordance         with S13.1.2, as is described with reference to FIGS. 16 and 17         FIGS. 16 & 17     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,0 701: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 701;     -   S13.2 Assess whether the region of interest requires cropping:         x2>X2_Q so set x2=X2_Q and y2>Y2_Q so set y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case (FIG. 17) both         conditions are satisfied, which means that there are no points         in sub-quad 0,0 (701) that fall within the region of interest;     -   S13.6 Increment sub-quad counter i at this level (0,i), and         retrieve sub-quad (0,1) in accordance with S13.1.2, as described         with reference to FIGS. 18 and 19.         FIGS. 18 & 19     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,1: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,1;     -   S13.2 Assess whether the region of interest requires cropping:         x1<X1_Q so set x1=X1_Q and y2>Y2_Q so set y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case neither         conditions are satisfied;     -   S13.4 Assess whether the region of interest (now cropped)         overlaps exactly with the sub-quad. No:     -   S13.5 Retrieve a sub-quad 0,1,0 of the present sub-quad 0,1 in         accordance with S13.1.2, as is described with reference to FIGS.         20 a and 20 b.         FIGS. 20 a & 20 b     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,1,0: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,1,0;     -   S13.2 Assess whether the region of interest requires cropping:         x2>X2_Q so set x2=X2_Q and y2>Y2_Q so set y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case (FIG. 20 b)         both conditions are satisfied, which means that there are no         points in sub-quad 0,1,0 that fall within the region of         interest;     -   S13.6 Increment sub-quad counter i at this level (0,1,i), and         (S13.6.1) retrieve sub-quad (0,1,1) in accordance with S13.1.2,         as is described with reference to FIGS. 21 a and 21 b.         FIGS. 21 a & 21 b     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,1,1: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,1,1—i.e. a single         point;     -   S13.2 Assess whether the region of interest requires cropping:         x1<X1_Q so set x1=X1_Q and y2>Y2_Q so set y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case (FIG. 21 b)         both conditions are satisfied, which means that there are no         points in sub-quad 0,1,1 that fall within the region of         interest;     -   S13.6 Increment sub-quad counter i at this level (0,1,i), and         (S13.6.1) retrieve sub-quad (0,1,2) in accordance with S13.1.2,         as is described with reference to FIGS. 22 a and 22 b.         FIGS. 22 a & 22 b

S13.1.2 Retrieve co-ordinates of points and size of sub-quad from “shrink-wrapped” sub-quad 0,1,2: set (X1_Q, Y1_Q) (X2_Q, Y2_Q) to size of “shrink-wrapped” sub-quad 0,1,2—i.e. a single point;

-   -   S13.2 Assess whether the region of interest requires cropping:         x1<X1_Q so set x1=X1_Q, y1<Y1_Q, x2>X2_Q and y2>Y2_Q so set         x1=X1_Q, y1=Y1_Q, x2=X2_Q, y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. No     -   S13.4 Assess whether the region of interest (now cropped)         overlaps exactly with the sub-quad: YES (as noted at S13.4.1 in         FIG. 13 b)     -   S13.4.2 Record the sub-quad and number of points within the         sub-quad (here 1);     -   S13.6 Increment sub-quad counter i at this level (0,1,i), and         (S13.6.1) retrieve sub-quad (0,1,3) in accordance with S13.1.2,         as is described with reference to FIGS. 23 a and 23 b.         FIGS. 23 a & 23 b     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,1,3: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,1,3—i.e. a single         point;     -   S13.2 Assess whether the region of interest requires cropping:         x1<X1_Q so set x1=X1_Q, y1<Y1_Q, x2>X2_Q and y2>Y2_Q so set         x1=X1_Q, y1=Y1_Q, x2=X2_Q, y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. No     -   S13.4 Assess whether the region of interest (now cropped)         overlaps exactly with the sub-quad: YES     -   S13.4.2 Record the sub-quad and number of points within the         sub-quad (here 1);     -   S13.6 Increment sub-quad counter i at this level (0,1,i) . . .         i>3 so (S13.6.2) retrieve sub-quad (0,2) in accordance with         S13.1.2, as is described with reference to FIGS. 24 and 25.         FIGS. 24 & 25     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,2: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,2;     -   S13.2 Assess whether the region of interest requires cropping:         y1<Y1_Q so set y1=Y1_Q and x2>X2_Q so set x2=X2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case neither         conditions are satisfied;     -   S13.4 Assess whether the region of interest (now cropped)         overlaps exactly with the sub-quad. No:     -   S13.5 Retrieve a sub-quad 0,2,0 of the present sub-quad 0,2 in         accordance with     -   S13.1.2, as is described with reference to FIGS. 26 a and 26 b.         FIGS. 26 a & 26 b     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,2,0: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,2,0;     -   S13.2 Assess whether the region of interest requires cropping:         x2>X2_Q so set x2=X2_Q and y2>Y2_Q so set y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case (FIG. 26 b)         both conditions are satisfied, which means that there are no         points in sub-quad 0,2,0 that fall within the region of         interest;     -   S13.6 Increment sub-quad counter i at this level (0,2,i), and         (S13.6.1) retrieve sub-quad (0,2,1) in accordance with S13.1.2,         as is described with reference to FIGS. 27 a and 27 b.         FIGS. 27 a & 27 b     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,2,1: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,2,1—i.e. a single         point;     -   S13.2 Assess whether the region of interest requires cropping:         x1<X1_Q so set x1=X1_Q, y1<Y1_Q, x2>X2_Q and y2>Y2_Q so set         x1=X1_Q, y1=Y1_Q, x2=X2_Q, y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. No     -   S13.4 Assess whether the region of interest (now cropped)         overlaps exactly with the sub-quad: YES     -   S13.4.2 Record the sub-quad and number of points within the         sub-quad (here 1);     -   S13.6 Increment sub-quad counter i at this level (0,1,i) . . .         i<3 so (S13.6.1) retrieve sub-quad (0,2,2) in accordance with         S13.1.2, as is described with reference to FIGS. 28 a and 28 b.         FIGS. 28 a & 28 b     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,2,2: set (X1_Q, Y1_Q) (X2_Q,         Y2_Q) to size of “shrink-wrapped” sub-quad 0,2,2;     -   S13.2 Assess whether the region of interest requires cropping:         x2>X2_Q so set x2=X2_Q and y1<Y1_Q so set y1=Y1_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. In this case (FIG. 28 b)         both conditions are satisfied, which means that there are no         points in sub-quad 0,2,2 that fall within the region of         interest;     -   S13.6 Increment sub-quad counter i at this level (0,2,i), and         (S13.6.1) retrieve sub-quad (0,2,3) in accordance with S13.1.2,         as is described with reference to FIG. 29.         FIG. 29     -   S13.1.2 Retrieve co-ordinates of points and size of sub-quad         from “shrink-wrapped” sub-quad 0,2,3: there is no sub-quad         corresponding to 0,2,3 because there are no points in the area         corresponding to this sub-quad, so jump to S13.6     -   S13.6.2 Increment sub-quad counter i at this level (0,2,i): i>3,         so (S13.6.2) retrieve sub-quad (0,3) in accordance with S13.1.2,         as is described with reference to FIGS. 30 and 31.         FIGS. 30 & 31     -   S13.2 Assess whether the region of interest requires cropping:         x1<X1_Q so set x1=X1_Q, y1<Y1_Q, x2>X2_Q and y2>Y2_Q so set         x1=X1_Q, y1=Y1_Q, x2=X2_Q, y2=Y2_Q;     -   S13.3 Assess whether x1>x2 or y1>y2. No     -   S13.4 Assess whether the region of interest (now cropped)         overlaps exactly with the sub-quad: YES     -   S13.4.2 Record the sub-quad and number of points within the         sub-quad (here 2);     -   S13.6 Increment sub-quad counter i at this level (0,i) . . . i>3         so (S13.6.2) retrieve sub-quad 1 in accordance with S13.1.2.         As can be seen from FIG. 14, the region of interest falls solely         within sub-quad 0 and the sub-quads therein, such that when         process described in FIGS. 13 a and 13 b is applied to sub-quads         1, 2 and 3, the conditions applied at steps S13.2 and S13.3 will         cause the process to terminate within a few steps.

At the end of the process of identifying sub-quads overlapping with the region of interest, the sub-quads, and the number of points within those sub-quads, that were recorded at steps S13.4.2 are returned—for this example:

sub-quad 0,1,2 number of points: 1 point;

sub-quad 0,1,3 number of points: 1 point;

sub-quad 0,2,1 number of points: 1 point;

sub-quad 0,3 number of points: 2 points.

Once the sub-quads have been identified, the actual points are retrieved. In this embodiment, and as described above, the points are stored in a flat file. Furthermore each sub-quad structure stores a number indicating the position, relative to the total number of points being indexed (Referring for example to FIG. 4, all of the points within quad 501), of the first point within a respective sub-quad.

The process for actual retrieval of points is shown in FIG. 32:

For each quad that was recorded at step S13.4.2:

-   -   S32.1 For that sub-quad retrieve number of points falling within         sub-quad (N);     -   S32.2 Retrieve position of the first point from the         corresponding sub-quad structure (Pos_(sub) _(—) _(quad));     -   S32.3 Move a file pointer to a position in the points file given         by Pos_(sub) _(—) _(quad);     -   S32.4 From this position, extract N points from the file.         Implementation

The processes described in FIGS. 4 a and 4 b, FIGS. 13 a and 13 b and FIG. 32 are implemented in software, and run on one of, or distributed between, the terminals T3, T4. Terminals T3, T4 are thus representative of one or a plurality of computers, and are preferably server computers.

Points to be indexed can be input to terminals T3, T4 via a file or similar, the index created as described above can be stored in the database DB1, and the points file can also be stored in the database DB1. An area of interest can be input in the form of a database query, entered via a client terminal (not shown) and communicated over the network N1 to terminals T3, T4 in a known manner.

Preferably the processes described above are implemented in the C programming language, and use recursive programming methods to “burrow down” to sub-quads within sub-quads. It is understood that such a method is inessential to the invention.

Additional Details and Modifications

As stated above, the invention can be used to index and retrieve data that is expressed in 2 dimensions. The invention can also be used to index and retrieve data of more than 2 dimensions, providing the data (n-dimensional data, where n>2) can be transformed into 2-dimensions. In such cases the transformed, 2-dimensional, data can be indexed and retrieved according to the invention. For example, objects defined in 3-dimensional space can be transformed into 2-dimensions using a package such as NCAR Graphics, which is a Unix based graphics package that offers a wide range of capabilities for the display and manipulation of numerical data, and has been developed by the University Corpocation for Atmospheric Research. (See http://www.dkrz.de/ngdoc/ng4.0.1 for information relating to NCAR graphics and http://ngwww.ucar.edu/ngdoc/ng/fund/chp16-21/threed.html for information relating to the 3 to 2 dimensional transformation aspects).

Other variations could be made. For instance, a simple one would be to use division of quads and sub-quads into different numbers of areas in each iteration, such as eight or ten instead of four. 

1. A method of building an index to a plurality of entities, wherein each entity is represented by data identifying a point defined in a space, by creating a hierarchy of sub-area data structures, the method comprising: (i) creating a region around the points representing the entities; (ii) performing a process in respect of the created region or sub-region, the process comprising: creating an area or sub-area data structure; storing, within the area or sub-area data structure, data specifying the extent of the respective region or sub-region; storing, within the area or sub-area data structure, links to points falling within the respective region or sub-region; dividing the region or sub-region to create a plurality of sub-regions; and for each of the plurality of sub-regions that contains points, reducing the sub-region until further reduction thereof would result in one of the points falling outside of the sub-region; and (iii) repeatedly performing the process in respect of each created sub-region that contains points until a predetermined criterion has been satisfied; wherein the method further comprises storing, within each area or sub-area data structure, links to sub-area data structures corresponding to its respective plurality of sub-regions; and wherein the hierarchy of sub-area data structures provides the index to the entities.
 2. A method as in claim 1, in which the predetermined criterion is that a sub-region includes a single point.
 3. A method as in claim 1, in which the step of reducing the region comprises: calculating distances between points corresponding to entities in each of two dimensions; and for each of the dimensions, identifying which of the points has the greatest distance between them, such that when the two dimensions are perpendicular to one another the region created is a rectangle, defined by points corresponding to at least two entities.
 4. A method as in claim 1, in which the region is divided into four sub-regions.
 5. A method as in claim 1, in which steps (ii) and (iii) are repeated recursively.
 6. A method as in claim 1, including storing the entities in a database, maintaining a register of number of entities stored in the database, and for each sub region, writing the current register number to the sub-area data structure corresponding thereto.
 7. A method as in claim 6, in which entities are written to the database in accordance with size of sub-region, such that entities falling within the smallest sub-regions are written to the database first.
 8. A method as in claim 1, including receiving a trigger signal for invoking steps (i) to (iii).
 9. A method of retrieving at least one entity that is contained within a predetermined area, wherein the at least one entity has been indexed by a method as in claim 1, including: (a) identifying one or more regions that are contained by the predetermined area, each region encompassing at least one point and being associated with linking data which, for each region, identifies the at least one point encompassed by that region; and (b) accessing linking data corresponding to the identified regions so as to retrieve points encompassed by the identified regions.
 10. A method as in claim 9, in which the identifying step (a) includes: (i) retrieving data identifying a region; (ii) performing a process in respect of the region, the process comprising the steps of: comparing extents of the region with extents of the predetermined area in order to establish whether the region overlaps with the predetermined area; if there is overlap, retrieving data identifying sub-regions of the region and identifying any such sub-regions whose extents are wholly within the predetermined area; and (iii) for each sub-region, repeating the process until all sub-regions thereof falling wholly within the predetermined area are identified, and the accessing step (b) involves accessing linking data corresponding to the identified sub-regions so as to retrieve points encompassed by the sub-regions.
 11. A method as in claim 10, wherein the plurality of points is pre-stored as a list of points in accordance with relationships between respective regions and sub-regions thereof, and the linking data includes a value indicating the position of a first of the corresponding encompassed points in the list of points, and wherein the accessing step (b) comprises, for each of the identified regions: retrieving an identifier representative of the number of encompassed points and retrieving a position value associated with the identified region; accessing the list of points and retrieving the number of encompassed points from a position in the list given by the position value.
 12. A method as in claim 9, in which the regions and corresponding linking data are stored in an index.
 13. A method as in claim 9, in which the predetermined area corresponds to range information.
 14. A method as in claim 13, in which the range information includes any one of geographical range information, operating hours information, delivery time information, and/or medical information.
 15. A computer program storage medium containing a computer program comprising a set of instructions which, when executed on a computer, or a suite of computers, perform the method according to claim
 9. 16. A computer program storage medium containing a computer program comprising a set of instructions which, when executed on-a computer, or a suite of computers, perform the method according to claim
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